Obesity Diminished: Patients Stay Aligned With Weight Loss Programs
Overview
Adherence is crucial for realizing the full benefits of a weight loss intervention. Although numerous studies have explored factors that promote adherence, their findings are often inconsistent and fragmented. This study aims to review existing adherence factors in weight loss interventions and identify elements that can inform the design of effective programs. A comprehensive search across six databases yielded 21 studies for this umbrella review. A total of 47 adherence factors were identified and categorized into six groups: (i) sociodemographic (n = 7), (ii) physical activity (n = 2), (iii) dietary (n = 8), (iv) pharmacological (n = 3), (v) multi-intervention (n = 23), and (vi) behavioral (n = 4). Additionally, a map of adherence factors was created.
Key findings indicate that personalized intervention strategies tailored to specific demographic characteristics are recommended. Self-monitoring proved effective across behavioral, dietary, and multi-interventions, while technology showed promise in enhancing adherence in dietary, behavioral, and multi-intervention contexts. Multi-interventions emerged as particularly effective adherence-promoting strategies, though further evidence is needed regarding pharmacological interventions. Overall, the identified adherence factors can be controlled and adjusted by researchers and practitioners to enhance adherence to weight loss interventions.
Introduction
Overweight and obesity have emerged as significant global health issues, with projections indicating that by 2030, 20% of the global population will be affected by obesity. This rise in obesity has resulted in substantial economic burdens and adverse health outcomes worldwide. Individuals with overweight and obesity face elevated risks of various diseases and serious health conditions, with obesity-related mortality rates increasing by approximately 20%, and rates for morbid obesity being even higher.
The trend of increasing overweight and obesity is now also evident in low- and middle-income countries, further exacerbating the economic impacts globally. If current trends persist, these impacts are expected to intensify over time. Managing obesity requires a comprehensive approach due to its association with multiple chronic and comorbid medical conditions. Prior research has proposed various intervention strategies to achieve and sustain significant short-term weight loss, such as reducing energy intake, altering the energy composition of food, boosting thermogenesis and energy expenditure through exercise or non-exercise activities, and employing pharmacological treatments when necessary.
However, these interventions often encounter challenges, as they tend to yield disappointing results and diminished effectiveness over the medium and long term, primarily due to low adherence rates. Adherence to weight loss programs is crucial for long-term success. The World Health Organization defines adherence as “the extent to which a person’s behavior, taking medication, following a diet, and/or making lifestyle changes, corresponds with agreed recommendations from a healthcare provider.” This broad definition presents challenges in the context of weight loss programs, which often involve multifactorial approaches with various components (diet, physical activity, psychotherapy, pharmacotherapy, etc.), leading to diverse methods of assessing adherence. Consequently, adherence to these programs is not consistently evaluated in a standardized manner (attrition, attendance, adherence to the diet, retention, self-monitoring, dropout, etc.), complicating the understanding and comparison of different factors affecting adherence.
Previous meta-analyses and systematic reviews have primarily focused on adherence factors in lifestyle interventions, with few studies examining adherence factors for other types of weight loss interventions. Additionally, some studies have sought to identify predictors of attrition and dropout. Despite the substantial number of meta-analyses and systematic reviews published in recent years, there has been no systematic summary and critical appraisal of this body of evidence. This lack of synthesis can lead to confusion among practitioners and researchers across different disciplines due to conflicting and scattered findings.
Therefore, an umbrella review is necessary to synthesize the most important and determining factors that enhance adherence levels among individuals with overweight and obesity participating in various weight loss programs. Identifying adherence and dropout factors can help design more effective programs by tailoring them to participants’ characteristics, thereby increasing attendance and maximizing individual-level effects.
Method
An umbrella review was performed adhering to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines and the Joanna Briggs Institute manual. All stages of the review were conducted in duplicate, and the study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) under the registration number CRD42022326218.
Two researchers (DW and MAR) independently identified studies up to April 13, 2022, across six electronic databases: Web of Science, PubMed/MEDLINE, Cochrane Library, Scopus, SPORTDiscus, and Embase. To address the question, “What are the factors in current research that improve adherence to weight loss programs?” the following combination of descriptors was used: (i) Obese OR Obesity OR Overweight; (ii) Weight OR bodyweight OR “Body Weight Change” OR BMI OR “body composition” OR fatness; (iii) Adhere* OR Nonadher* OR “Non-adhere*” OR complian* OR Noncomplian* OR “Non-complian*”; and (iv) “meta-an*” OR “systematic review”. A systematic search strategy was developed using the PICOS strategy. Data extraction followed prior recommendations for umbrella reviews, with information extracted using pre-designed Microsoft Office Excel forms. Two researchers independently extracted key details from each included study, including basic study information, search dates, databases searched, the number of included studies, total participants, study designs, tools for assessing risk of bias, participant demographics, and a general summary for each outcome.
The methodological quality and risk of bias of the selected studies were evaluated using The Assessment of Methodological Quality of Systematic Reviews (AMSTAR-2). Two reviewers (DW and MAR) conducted the assessment independently, reaching consensus through discussion or with the help of a third reviewer if necessary. The AMSTAR-2 checklist includes 16 items, each answered with “yes,” “no,” “cannot answer,” or “not applicable.” Only “yes” answers contributed to the total score. Reviews were categorized into four levels based on the AMSTAR-2 criteria: high confidence (no or one non-critical defect), medium confidence (more than one non-critical defect), low confidence (defects which are critical without or with non-critical defects), and critically low confidence (greater than one critical defect without or with non-critical defects).
All extracted data were qualitatively analyzed and presented narratively, as no meta-analysis was performed due to the heterogeneity in definitions, measurements, and outcomes across studies.
Inclusion Criteria
Eligibility criteria included systematic reviews and systematic reviews with meta-analysis analyzing all types of weight loss interventions, except surgeries. Studies were included if they involved participants over 18 years of age (overweight with BMI > 25 kg/m² or obese with BMI > 30 kg/m²) and interventions comprising behavioral, pharmacological, psychological, or multi-intervention strategies for weight loss. Studies required at least one control group and focused on identifying factors associated with adherence to the intervention, barriers to lifestyle interventions, or predictors of adherence or attrition. Adherence had to be one of the primary outcomes, measured by objective or self-reported changes in physical activity and/or diet or attendance to intervention sessions.
Exclusion Criteria
Studies were excluded if they involved populations with pathologies unrelated to metabolic syndrome or obesity, were not peer-reviewed journal articles, or were written in languages other than English.
Result
The review process involved 4,758 records sourced from bibliographic databases. After removing 1,624 duplicates, 3,134 studies were initially selected based on their titles and abstracts. Of these, 3,034 were deemed irrelevant and excluded. The remaining 94 studies underwent full-text review for eligibility, with 73 being excluded for various reasons, as detailed in Supplementary Table 2. This process left 21 systematic reviews eligible for inclusion in the umbrella review.
The quality of the included reviews was evaluated using the AMSTAR-2 assessment tool. The results, presented in Supplementary Table 3, revealed numerous methodological flaws. Four reviews were rated as “low” quality, five as “moderate,” and twelve as “critically low.” Key issues contributing to these ratings included inadequate assessment of individual risk of bias in only eight reviews, methodological limitations such as the absence of protocols or pre-registration, and insufficient justification for exclusions in several studies.
The 21 systematic reviews and meta-analyses were published in the past 15 years (post-2008). Among them, eight were systematic reviews, ten combined systematic reviews with meta-analyses, two were meta-analyses, and one was an overview. The number of studies reviewed ranged from seven to 103, with a total sample size of 36,805 participants aged 18 to 65, though some studies did not report age. Of these studies, 13 predominantly included female participants. Most studies reported a body mass index (BMI) over 25 kg/m², with a few exceptions exceeding 30 kg/m². The studies were primarily from the United States, with contributions from Europe, Australia, Turkey, and Asia.
The reviews covered various topics:
– Four focused on adherence to behavioral weight management.
– Three on adherence to diet.
– Two on adherence and attrition in pharmacological interventions.
– Four examined facilitators and barriers to adherence.
– Eight explored different intervention types and their impact on adherence, including behavior contracts, self-monitoring, technology-based interventions, and financial incentives.
Definitions of adherence varied across studies, with terms such as “adherence,” “attrition,” “dropout,” and “retention” used interchangeably. Measurements often focused on percentages related to these concepts. Behavioral contracts were found effective in promoting dietary changes and adherence both in the short term (≤6 months) and long term (>12 months). Online dietary interventions improved eating behaviors and reduced dropout rates. Food supplements, when combined with dietary advice and regular monitoring, were also noted to enhance adherence.
Inconsistent results emerged regarding intermittent fasting, with some studies showing low dropout rates while others reported poor long-term adherence. No clear associations were found between dropout rates and factors like population type or dietary goals.
Three key factors influenced pharmacological intervention adherence:
– Specific medications, such as sibutramine and orlistat.
– The completion of a pre-randomization introduction period.
– Gender, with females showing higher attrition rates. Sibutramine, in particular, was associated with better adherence and lower dropout rates compared to other medications.
Self-monitoring, financial incentives, and supervised programs were identified as the most effective behavioral strategies. Self-monitoring using mobile health tools showed lower dropout rates compared to traditional methods. Financial incentives, especially when combined with other behavioral interventions, improved adherence. Supervised programs also demonstrated higher adherence rates compared to unsupervised ones.
Multicomponent approaches, combining physical activity, nutrition, and self-monitoring, were effective in reducing attrition. Programs integrating multiple behavioral strategies and techniques also showed improved adherence.
Factors such as early weight loss success, greater weight loss, healthier eating, and physical activity positively influenced adherence. Psychological factors, including mood, motivation, and social support, were also important. Conversely, predictors of attrition included body shape concerns, unrealistic weight loss expectations, lower initial weight loss, depression, stress, previous weight loss attempts, and financial difficulties. Results regarding self-efficacy and motivation were mixed.
Conclusion
This umbrella review presents the first extensive synthesis of adherence factors in weight loss programs over the past 15 years. It highlights variables influencing adherence and evaluates data from 21 reviews to create an adherence map aimed at optimizing interventions.
There is no single term or definition that encompasses all aspects of adherence in weight loss programs. The review advocates for establishing a unified consensus on definitions and frameworks to guide clinical research and practice.
The review identified 47 factors impacting adherence, categorized into multi-intervention and behavioral strategies, with fewer related to physical activity. Two main insights emerged:
– Self-Monitoring: Enhancing self-monitoring is crucial for improving adherence.
– Intervention Types: Multi-component or behavioral interventions should be prioritized, considering demographic factors when designing programs, especially for disadvantaged groups.
Factors like gender, age, education, and body characteristics affect adherence. It is important to tailor interventions based on these factors, recognizing which are modifiable and which are not.
Acceptance and Commitment Therapy (ACT) is effective in increasing adherence to physical activity by enhancing psychological flexibility, which helps in maintaining behavior changes.
Self-monitoring significantly boosts adherence in dietary interventions. However, long-term adherence remains challenging, as adherence to dietary self-monitoring tends to decline over time.
Medications like sibutramine and orlistat were associated with lower dropout rates, though sibutramine has been banned due to safety concerns. Orlistat remains a viable option, showing fewer adverse effects and better adherence outcomes compared to other medications.
Self-monitoring and financial incentives are effective in improving adherence. Technology aids in easier and more convenient self-monitoring, which is essential for adherence.
Combining multiple intervention strategies, such as behavioral, psychological, and lifestyle changes, proves more effective in promoting adherence. Multi-component and multi-approach interventions address various barriers to adherence more comprehensively.
The review’s strength lies in its comprehensive approach, consolidating evidence from numerous studies to guide program design. However, limitations include methodological differences among studies and the lack of standardized adherence definitions, which hinder direct comparisons and meta-analysis.
In conclusion, the review emphasizes the importance of multi-intervention strategies, self-monitoring, and financial incentives in weight loss programs. It calls for further research to standardize adherence definitions and explore additional factors influencing adherence to optimize weight loss interventions.
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